{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x23f62ed6eb8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from sklearn import datasets\n",
    "from sklearn import linear_model\n",
    "%matplotlib inline\n",
    "\n",
    "matplotlib.rcParams['figure.figsize'] = (10.0, 8.0)\n",
    "\n",
    "np.random.seed(0)\n",
    "X,y = datasets.make_moons(200, noise=0.2)\n",
    "plt.scatter(X[:,0], X[:,1], s=40, c=y, cmap=plt.cm.Spectral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\Anaconda3\\lib\\site-packages\\sklearn\\model_selection\\_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegressionCV(Cs=10, class_weight=None, cv='warn', dual=False,\n",
       "                     fit_intercept=True, intercept_scaling=1.0, l1_ratios=None,\n",
       "                     max_iter=100, multi_class='warn', n_jobs=None,\n",
       "                     penalty='l2', random_state=None, refit=True, scoring=None,\n",
       "                     solver='lbfgs', tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the logistic regression classifier\n",
    "clf = linear_model.LogisticRegressionCV()\n",
    "clf.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_decision_boundary(pred_func):\n",
    "    # Set min and max values and give it some padding\n",
    "    x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\n",
    "    y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\n",
    "    h = 0.01\n",
    "    # Generate a grid of points with distance h between them\n",
    "    xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
    "    # Predict the function value for the whole gid\n",
    "    Z = pred_func(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "    # Plot the contour and training examples\n",
    "    plt.contourf(xx, yy, Z, cmap=plt.cm.Spectral)\n",
    "    plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Spectral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Logistic Regression')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the decision boundary\n",
    "plot_decision_boundary(lambda x: clf.predict(x))\n",
    "plt.title(\"Logistic Regression\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_examples = len(X) # training set size\n",
    "nn_input_dim = 2 # input layer dimensionality\n",
    "nn_output_dim = 2 # output layer dimensionality\n",
    "\n",
    "# Gradient descent parameters (I picked these by hand)\n",
    "epsilon = 0.01 # learning rate for gradient descent\n",
    "reg_lambda = 0.01 # regularization strength"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper function to evaluate the total loss on the dataset\n",
    "def calculate_loss(model):\n",
    "    W1, b1, W2, b2 = model['W1'], model['b1'], model['W2'], model['b2']\n",
    "    z1 = X.dot(W1) + b1\n",
    "    a1 = np.tanh(z1)\n",
    "    z2 = a1.dot(W2) + b2\n",
    "    exp_scores = np.exp(z2)\n",
    "    probs = exp_scores / np.sum(exp_scores, axis=1, keepdims=True)\n",
    "    # Calculating the loss by Cross Entropy\n",
    "    corect_logprobs = -np.log(probs[range(num_examples), y])#Cross Entropy\n",
    "    data_loss = np.sum(corect_logprobs)\n",
    "    # Add regulatization term to loss (optional)\n",
    "    data_loss += reg_lambda/2 * (np.sum(np.square(W1)) + np.sum(np.square(W2))) #regularize theta\n",
    "    return 1./num_examples * data_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper function to predict an output (0 or 1)\n",
    "#Using Softmax;\n",
    "def predict(model, x):\n",
    "    W1, b1, W2, b2 = model['W1'], model['b1'], model['W2'], model['b2']\n",
    "    # Forward propagation\n",
    "    z1 = x.dot(W1) + b1\n",
    "    a1 = np.tanh(z1)\n",
    "    z2 = a1.dot(W2) + b2\n",
    "    exp_scores = np.exp(z2)\n",
    "    probs = exp_scores / np.sum(exp_scores, axis=1, keepdims=True)\n",
    "    return np.argmax(probs, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This function learns parameters for the neural network and returns the model.\n",
    "# - nn_hdim: Number of nodes in the hidden layer\n",
    "# - num_passes: Number of passes through the training data for gradient descent\n",
    "# - print_loss: If True, print the loss every 1000 iterations\n",
    "def build_model(nn_hdim, num_passes=20000, print_loss=False):\n",
    "    \n",
    "    # Initialize the parameters to random values. We need to learn these.\n",
    "    np.random.seed(0)\n",
    "    W1 = np.random.randn(nn_input_dim, nn_hdim) / np.sqrt(nn_input_dim)\n",
    "    b1 = np.zeros((1, nn_hdim))\n",
    "    W2 = np.random.randn(nn_hdim, nn_output_dim) / np.sqrt(nn_hdim)\n",
    "    b2 = np.zeros((1, nn_output_dim))\n",
    "\n",
    "    # This is what we return at the end\n",
    "    model = {}\n",
    "    \n",
    "    # Gradient descent. For each batch...\n",
    "    for i in range(0, num_passes):\n",
    "\n",
    "        # Forward propagation\n",
    "        z1 = X.dot(W1) + b1\n",
    "        a1 = np.tanh(z1)\n",
    "        z2 = a1.dot(W2) + b2\n",
    "        exp_scores = np.exp(z2)\n",
    "        probs = exp_scores / np.sum(exp_scores, axis=1, keepdims=True)\n",
    "        # Backpropagation\n",
    "        delta3 = probs\n",
    "        delta3[range(num_examples), y] -= 1\n",
    "        dW2 = (a1.T).dot(delta3)\n",
    "        db2 = np.sum(delta3, axis=0, keepdims=True)\n",
    "        delta2 = delta3.dot(W2.T) * (1 - np.power(a1, 2))\n",
    "        dW1 = np.dot(X.T, delta2)\n",
    "        db1 = np.sum(delta2, axis=0)\n",
    "\n",
    "        # Add regularization terms (b1 and b2 don't have regularization terms)\n",
    "        dW2 += reg_lambda * W2\n",
    "        dW1 += reg_lambda * W1\n",
    "\n",
    "        # Gradient descent parameter update\n",
    "        W1 += -epsilon * dW1\n",
    "        b1 += -epsilon * db1\n",
    "        W2 += -epsilon * dW2\n",
    "        b2 += -epsilon * db2\n",
    "        \n",
    "        # Assign new parameters to the model\n",
    "        model = { 'W1': W1, 'b1': b1, 'W2': W2, 'b2': b2}\n",
    "        \n",
    "        # Optionally print the loss.\n",
    "        # This is expensive because it uses the whole dataset, so we don't want to do it too often.\n",
    "        if print_loss and i % 1000 == 0:\n",
    "          print(\"Loss after iteration %i: %f\" %(i, calculate_loss(model)))\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss after iteration 0: 0.432387\n",
      "Loss after iteration 1000: 0.068947\n",
      "Loss after iteration 2000: 0.068890\n",
      "Loss after iteration 3000: 0.071218\n",
      "Loss after iteration 4000: 0.071253\n",
      "Loss after iteration 5000: 0.071278\n",
      "Loss after iteration 6000: 0.071293\n",
      "Loss after iteration 7000: 0.071303\n",
      "Loss after iteration 8000: 0.071308\n",
      "Loss after iteration 9000: 0.071312\n",
      "Loss after iteration 10000: 0.071314\n",
      "Loss after iteration 11000: 0.071315\n",
      "Loss after iteration 12000: 0.071315\n",
      "Loss after iteration 13000: 0.071316\n",
      "Loss after iteration 14000: 0.071316\n",
      "Loss after iteration 15000: 0.071316\n",
      "Loss after iteration 16000: 0.071316\n",
      "Loss after iteration 17000: 0.071316\n",
      "Loss after iteration 18000: 0.071316\n",
      "Loss after iteration 19000: 0.071316\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Decision Boundary for hidden layer size 3')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build a model with a 3-dimensional hidden layer\n",
    "model = build_model(3, print_loss=True)\n",
    "\n",
    "# Plot the decision boundary\n",
    "plot_decision_boundary(lambda x: predict(model, x))\n",
    "plt.title(\"Decision Boundary for hidden layer size 3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
